James Gunning

1.2k total citations
66 papers, 749 citations indexed

About

James Gunning is a scholar working on Geophysics, Ocean Engineering and Mechanical Engineering. According to data from OpenAlex, James Gunning has authored 66 papers receiving a total of 749 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Geophysics, 36 papers in Ocean Engineering and 24 papers in Mechanical Engineering. Recurrent topics in James Gunning's work include Seismic Imaging and Inversion Techniques (32 papers), Reservoir Engineering and Simulation Methods (28 papers) and Hydraulic Fracturing and Reservoir Analysis (21 papers). James Gunning is often cited by papers focused on Seismic Imaging and Inversion Techniques (32 papers), Reservoir Engineering and Simulation Methods (28 papers) and Hydraulic Fracturing and Reservoir Analysis (21 papers). James Gunning collaborates with scholars based in Australia, United States and United Kingdom. James Gunning's co-authors include Michael E. Glinsky, Derek Y. C. Chan, Steven L. Carnie, M. Sams, J. N. Hedditch, Lee R. White, Lincoln Paterson, Brice Lecampion, Juerg Hauser and M.A. Addis and has published in prestigious journals such as Langmuir, Carbon and Journal of Colloid and Interface Science.

In The Last Decade

James Gunning

60 papers receiving 716 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
James Gunning Australia 17 434 379 273 115 95 66 749
Frank Dale Morgan United States 14 761 1.8× 463 1.2× 63 0.2× 184 1.6× 208 2.2× 55 1.1k
Christine E. Krohn United States 10 249 0.6× 294 0.8× 151 0.6× 75 0.7× 23 0.2× 27 649
Hongming Tang China 20 128 0.3× 453 1.2× 463 1.7× 55 0.5× 90 0.9× 77 1.3k
S. Békri France 22 304 0.7× 770 2.0× 462 1.7× 487 4.2× 90 0.9× 53 1.4k
Carl Fredrik Berg Norway 17 102 0.2× 474 1.3× 271 1.0× 149 1.3× 95 1.0× 76 1.0k
Matthew Josh Australia 15 275 0.6× 565 1.5× 437 1.6× 118 1.0× 41 0.4× 50 1.1k
Ching‐Yao Lai United States 12 64 0.1× 168 0.4× 108 0.4× 67 0.6× 64 0.7× 27 605
Jörg Renner Germany 19 899 2.1× 149 0.4× 182 0.7× 149 1.3× 37 0.4× 49 1.2k
Matthias Appel United States 17 98 0.2× 270 0.7× 169 0.6× 87 0.8× 64 0.7× 52 814
F. M. Auzerais United States 10 93 0.2× 225 0.6× 136 0.5× 89 0.8× 53 0.6× 16 592

Countries citing papers authored by James Gunning

Since Specialization
Citations

This map shows the geographic impact of James Gunning's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by James Gunning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Gunning more than expected).

Fields of papers citing papers by James Gunning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Gunning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by James Gunning. The network helps show where James Gunning may publish in the future.

Co-authorship network of co-authors of James Gunning

This figure shows the co-authorship network connecting the top 25 collaborators of James Gunning. A scholar is included among the top collaborators of James Gunning based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with James Gunning. James Gunning is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jackson, Samuel J., James Gunning, Jonathan Ennis‐King, Tess Dance, & Charles Jenkins. (2025). Towards industrial deployment of pressure tomography for CO2 storage monitoring: Uncertainty and megatonne scale-up. International journal of greenhouse gas control. 141. 104299–104299. 1 indexed citations
2.
Hauser, Juerg, et al.. (2025). Time-lapse inversion of airborne electromagnetic data to recover the evolution of interfaces between freshwater and saltwater. Geophysics. 90(5). E181–E190. 1 indexed citations
3.
Gunning, James, et al.. (2024). Automated lithofluid and facies classification in well logs: The rock-physics perspective. Geophysics. 89(4). MR209–MR222. 2 indexed citations
4.
Gunning, James, Samuel J. Jackson, Andrew Wilkins, et al.. (2024). Correction: A History Matching Study for the FluidFlower Benchmark Project. Transport in Porous Media. 151(5). 1141–1141.
5.
Butcher, Antony, J. M. Kendall, Thomas Hudson, et al.. (2023). DAS-N2N: machine learning distributed acoustic sensing (DAS) signal denoising without clean data. Geophysical Journal International. 236(2). 1026–1041. 16 indexed citations
6.
Gunning, James, et al.. (2021). Rock-physics machine learning toolkit for joint litho-fluid facies classification and compaction modeling. The Leading Edge. 40(10). 742–750. 4 indexed citations
7.
Jackson, Samuel J., et al.. (2021). Baseline monitoring for time-lapse pressure tomography: Initial results from Otway Stage 3. SSRN Electronic Journal. 2 indexed citations
8.
Hauser, Juerg, et al.. (2016). Probabilistic inversion of airborne electromagnetic data for basement conductors. Geophysics. 81(5). E389–E400. 5 indexed citations
9.
Hauser, Juerg, et al.. (2015). Probabilistic inversion of airborne electromagnetic data under spatial constraints. Geophysics. 80(2). E135–E146. 20 indexed citations
10.
Gunning, James, et al.. (2014). Obstacles, Challenges and Strategies for Facies Estimation in AVO Seismic Inversion. Proceedings. 1 indexed citations
11.
Hauser, Juerg, et al.. (2013). Probabilistic inversion of airborne electromagnetic data for a multidimensional earth. ASEG Extended Abstracts. 2013(1). 1–4. 1 indexed citations
12.
Gunning, James, Michael E. Glinsky, & J. N. Hedditch. (2010). Resolution and uncertainty in 1D CSEM inversion: A Bayesian approach and open-source implementation. Geophysics. 75(6). F151–F171. 35 indexed citations
13.
Glinsky, Michael E., et al.. (2008). Bayesian inversion whispers. The Leading Edge. 27(5). 642–649. 2 indexed citations
14.
Gunning, James & Michael E. Glinsky. (2007). Detection of reservoir quality using Bayesian seismic inversion. Geophysics. 72(3). R37–R49. 73 indexed citations
15.
Glinsky, Michael E., et al.. (2007). The value of using relative amplitude changes. The Leading Edge. 26(5). 562–569.
16.
Lecampion, Brice & James Gunning. (2006). Model selection in fracture mapping from elastostatic data. International Journal of Solids and Structures. 44(5). 1391–1408. 18 indexed citations
17.
Glinsky, Michael E., M. A. Stanley, James Gunning, et al.. (2005). Integration of uncertain subsurface information into multiple reservoir simulation models. The Leading Edge. 24(10). 990–999. 10 indexed citations
18.
Gunning, James & Michael E. Glinsky. (2005). Wavelet extractor: A Bayesian well-tie and wavelet extraction program. Computers & Geosciences. 32(5). 681–695. 22 indexed citations
19.
Pastina, Debora, Alfonso Farina, James Gunning, & P. Lombardo. (1998). Two-dimensional super-resolution spectralanalysis applied to SAR images. IEE Proceedings - Radar Sonar and Navigation. 145(5). 281–290. 20 indexed citations
20.
Gunning, James & Derek Y. C. Chan. (1994). Phonon Interaction Energy of an Elastic Layer on an Infinite Half Space Solid. Journal of Colloid and Interface Science. 163(1). 100–107. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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